Instructions to use bartowski/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use bartowski/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf bartowski/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf bartowski/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf bartowski/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf bartowski/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf bartowski/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf bartowski/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF:Q4_K_M
Use Docker
docker model run hf.co/bartowski/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF:Q4_K_M
- Llama new
- LM Studio
- Jan
- vLLM
How to use bartowski/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bartowski/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "bartowski/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/bartowski/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF:Q4_K_M
- Ollama
How to use bartowski/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF with Ollama:
ollama run hf.co/bartowski/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use bartowski/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF with Docker Model Runner:
docker model run hf.co/bartowski/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF:Q4_K_M
- Lemonade
How to use bartowski/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull bartowski/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF / smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-Q6_K.gguf
Download smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-Q6_K.gguf from bartowski/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 1.49 GB
-
https://huggingface.co/bartowski/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF/resolve/main/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-Q6_K.gguf
- Command line
-
hf download hf://bartowski/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-Q6_K.gguf
-
curl -L -o smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-Q6_K.gguf https://huggingface.co/bartowski/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-GGUF/resolve/main/smolagents_SmolVLM2-2.2B-Instruct-Agentic-GUI-Q6_K.gguf
1.49 GB
- Xet hash:
- 96792ba323b50334486d7d227ac689890a743cc764911eb0ad890d38430b2fdf
- Size of remote file:
- 1.49 GB
- SHA256:
- 1654561ce95c1b2494f67751aea2af68b88a6ebe7faf512455cbcd8741a36aba
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